By Topic

3D free-form object recognition in range images using local surface patches

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Hui Chen ; Center for Res. in Intelligent Syst., California Univ., Riverside, CA, USA ; Bir Bhanu

This paper introduces an integrated local surface descriptor for surface representation and object recognition. A local surface descriptor is defined by a centroid, its surface type and 2D histogram. The 2D histogram consists of shape indexes, calculated from principal curvatures, and angles between the normal of reference point and that of its neighbors. Instead of calculating local surface descriptors for all the 3D surface points, we only calculate them for feature points, which are areas with large shape variation. Furthermore, in order to speed up the search process and deal with a large set of objects, model local surface patches are indexed into a hash table. Given a set of test local surface patches, we cast votes for models containing similar surface descriptors. Potential corresponding local surface patches and candidate models are hypothesized. Verification is performed by aligning models with scenes for the most likely models. Experimental results with real range data are presented to demonstrate the effectiveness of our approach.

Published in:

Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on  (Volume:3 )

Date of Conference:

23-26 Aug. 2004